Network Pharmacology and Molecular Docking Analysis on Molecular Targets and Mechanisms of Aidi Injection Treating of Nonsmall Cell Lung Cancer

Background Aidi injection (ADI) is a compound preparation injection of Chinese herbs used to treat patients of nonsmall cell lung cancer (NSCLC) in China. This study aimed to reveal the mechanism of ADI in the treatment of NSCLC by using network pharmacology and molecular docking. Methods The related targets of ADI and NSCLC were obtained from multiple databases. The network diagram of disease-drug-components-targets (DDCT) and protein-protein interaction (PPI) was constructed to screen key targets. Then, the key targets and main signaling pathways were screened by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Next, in order to validate the results of network pharmacology, expression analysis and survival analysis of key genes were performed. Finally, we carried out the technology of molecular docking to further validate the accuracy of the above results. Results A total of 207 targets of ADI and 5282 targets of NSCLC were obtained finally. Through the construction of DDCT and PPI network diagrams, 28 key targets were finally obtained. The results of the KEGG enrichment analysis indicated that multiple signaling pathways were associated with NSCLC, which included the MAPK signaling pathway, the IL-17 signaling pathway, and the PI3K/AKT signaling pathway. The key genes in the signaling pathway mainly include TP53, CASP3, MMP9, AKT1, PTGS2, and MAPK1. The results of differently expressed analysis of key genes showed that TP53, CASP3, MMP9, AKT1, PTGS2, and MAPK1 had statistical differences in lung squamous cell carcinoma (LUSC) compared with normal tissue (p < 0.001). In lung adenocarcinoma (LUAD), the expression of TP53, CASP3, MMP9, AKT1, and PTGS2 had statistical differences compared with normal tissue (p < 0.001), while the expression of MAPK1 had no statistical difference (p > 0.05). The results of survival analysis of key genes showed that AKT1, MAPK1, CASP3, MMP9, TP53, and PTGS2 had statistical differences in the OS or RFS of NSCLC patients (p < 0.05). In addition, the results of molecular docking indicated that the key genes and the main components have good docking activity. Conclusions This study revealed the potential mechanism of ADI in the treatment of NSCLC with multipathways and multitargets and provided a scientific basis for the in-depth study of ADI in the treatment of NSCLC.


Introduction
Lung cancer is the leading cause of cancer-related deaths worldwide, with the 5-year survival less than 21% [1]. Nonsmall cell lung cancer (NSCLC) accounts for 85% of all lung cancers. Lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) are the two main pathological types of NSCLC [2]. In the early stages of lung cancer, it can be cured by surgery, and the treatment methods in the middle and late stages mainly include chemotherapy, radiotherapy, targeted therapy, and immunotherapy. However, since NSCLC generally has no obvious clinical symptoms in the early stage, it is often discovered during the chest impact examination, leading most patients to seek medical attention. It was already in the middle and late stages, and the opportunity for surgery was lost. With the successive identifcation of oncogenic driver genes in lung cancer series, molecular targeted therapy plays an important role in the treatment of advanced NSCLC, which has greatly improved the prognosis of people with positive driver genes. In recent years, with the major breakthrough of immunotherapy in the feld of lung cancer, the 5-year overall survival of some patients with negative driver genes has been signifcantly extended. However, due to the obvious adverse reactions of molecular targeted therapy and immunotherapy [3], easy drug resistance and high medical costs made it is still a refractory disease worldwide. At present, there are still many defciencies in the conventional treatment of NSCLC. Terefore, it is urgent to study the molecular mechanisms of NSCLC and fnd efcient and safe therapeutic drugs. In recent years, there have been more and more clinical trials and basic researches on the treatment of NSCLC with traditional Chinese medicine (TCM), which providing new ideas and methods for NSCLC treatment.
Aidi injection (ADI) is a compound preparation injection of Chinese herbs (Z52020236, CFDA), which is extracted from Mylabris (Banmao), Panax Ginseng (Renshen), Acanthopanax Senticosus (Ciwujia), and Astragali Radix (Huangqi), four traditional Chinese herbs [4]. In recent years, ADI combined with other antitumor drugs has been widely used in the treatment of NSCLC and has achieved good clinical efects. For example, ADI combined with chemotherapy (pemetrexed disodium and cisplatin or gemcitabine and cisplatin) had a positive efect in the treatment of NSCLC, which could efectively improve the Karnofsky performance status of patients, reduce the risk of adverse reactions, and improve the survival rate [5,6]. In addition, studies showed that ADI combined with geftinib had signifcant efcacy and high safety in the treatment of NSCLC [7,8]. Although the clinical efcacy of ADI is remarkable, its mechanism is still unclear and needs to be further explored.
Emphasizing the holistic concept when treating diseases with TCM, as a TCM injection preparation, the function of ADI naturally depends on the mutual coordination and complementation of each Chinese herb. In order to comprehensive inquiry the efect of ADI and reveal the mechanism of ADI in the treatment of NSCLC, we employed a network pharmacology strategy. Network pharmacology is a novel discipline based on the theory of systems biology, analyzing the network of biological systems and selecting specifc signaling nodes for multitargets drug molecular design [9]. Its research concept coincides with the holism of TCM and is widely used for the discovery of drugs and active compounds in TCM and the interpretation of the all-sided mechanism, providing new scientifc and technological support for clinical rational drug use and advancing drug research.

Potential Targets of ADI.
Te active ingredients and related targets of Panax Ginseng, Astragali Radix, and Mylabris were obtained from the TCMSP (https://tcmspw. com/tcmsp.php) database. Te active ingredients of senticosus were obtained from the TCMID (https://www. megabionet.org/tcmid/) database and then imported back into the TCMSP database one by one to obtain the related targets of senticosus. Screening conditions are oral bioavailability (OB) ≥30% and drug likeness (DL) ≥0.18.

NSCLC Related Targets.
Te NSCLC-related targets were obtained from the OMIM (https://omim.org/) and Gene-Cards Suite (https://www.genecards.org) databases, using nonsmall cell lung cancer or NSCLC as the search term. Merge all targets from the two databases and delete duplicate targets as the fnal target for NSCLC.

Intersecting Targets of ADI and NSCLC.
In order to obtain the intersecting targets and make a Venn diagram of ADI and NSCLC, the related targets of ADI and NSCLC obtained above were inputted into the Venny 2.1.0 (https:// bioinfogp.cnb.csic.es/tools/venny/index.html).

Construction of DDCT and PPI Network Diagrams.
Running the prepared Cyto.pl script through the Perl program to obtain the linkage network fle and classifcation fle of nodes, the active ingredient fle and the fle of the intersecting targets of ADI and NSCLC, and he above fles were imported into Cytoscape software (version 3.7.2) to build the DDCT network diagram. Te PPI linkage fle was obtained by using the intersecting targets of ADI and NSCLC in the STRING database (https://string-db.org). We imported the PPI linkage fle into Cytoscape software to create a PPI network diagram and screened out targets with a degree and betweenness centrality (BC) greater than their mean values as the key targets for the study.

GO and KEGG Enrichment Analysis.
Te selected key targets were entered into the DAVID database (https:// david.ncifcrf.gov/) for GO and KEGG enrichment analysis, and the species selected was "Homo sapiens." Te cluster profler package and the ggplot2 data package [10] were used to perform statistical analysis and visualization for the key targets through R software (Version 3.6.3), and the main biological processes and signaling pathways involved in the treatment of NSCLC by ADI were screened out with p adjust <0.05. Genes in major signaling pathways were regarded as key genes for further study.

Expression Analysis of Key Genes.
In order to explore the expression diferences of the screened key genes in tumor tissue and normal tissue, we downloaded the Level 3 RNAseq data in HTSeq-FPKM format of key genes in LUSC and LUAD from the TCGA (https://portal.gdc.cancer.gov/) database. Ten, the RNAseq data were converted in FPKM format to TPM format and log2 conversion. Te R (3.6.3) software and ggplot2 package were used for statistical analysis and visualization [11].

Survival Analysis of Key Genes.
To validate the results of network pharmacology, we used a survival analysis method to investigate whether the expression of key genes had an efect on survival rate with OS (overall survival) and RFS (relapse-free survival) as study indicators. Te Kaplan-Meier plotter (https://kmplot.com/analysis/) was used for this study, which is a powerful online tool for assessing the correlation between the expression and survival of 30,000 genes in more than 25,000 samples from 21 tumor types [12]. We split patients by median and automatically selected the best cutof. Survival analysis curves were plotted by a Kaplan-Meier plotter, and the logrankp < 0.05 was considered statistically signifcant.

Molecular Docking.
To further verify the above results, we performed molecular docking on key genes. To further verify the above results, we selected the top 10 active compounds in the DDCT network and key genes in the main signaling pathway for molecular docking. Te structures of the related active compounds and key genes were obtained from PubChem (https://pubchem.ncbi.nlm.nih.gov) and the RSCB PDB database (https://www.rcsb.org/), respectively. AutoDock Vina software (https://vina.scripps.edu/) was used to perform molecular docking of key proteins and active ingredients, and the afnity value represents the binding energy of both. It is generally believed that the lower the binding energy, the more stable the binding of active ingredients and proteins [13]. Te best conformation of afnity was selected as the fnal docking conformation and fnally plotted the best results obtained using PyMol software.
2.9. Statistical Methods. Te cluster profler and ggplot2 data packages of R software (Version 3.6.3) were used to perform statistical analysis on the results of enrichment analysis and gene expression diferences. To compare survival curves, we used the log-rank test to calculate the HR and log-rankp value in the Kaplan-Meier plotter. All results were considered statistically signifcant when p < 0.05, if not especially noted.

Results
In this study, network pharmacology was used to analyze the potential targets of ADI and NSCLC, and the Venn diagram was used to obtain intersecting targets for ADI and NSCLC at the same time. Next, to identify key targets, the intersecting targets of ADI and NSCLC were used to construct a network diagram of disease-drugcomponents-targets (DDCT) and protein-protein interactions (PPI). Ten, we obtained the main biological functions and signaling pathways involved in the ADI treatment of NSCLC through key targets. In order to verify the targets and signaling pathways obtained in previous, we performed diferential expression analysis and survival analysis of key genes in mainly signaling pathways. Finally, the molecular docking technique was used to further verify the above results. Te workfow chart of this study is shown in Figure 1.

Intersecting Targets of ADI and NSCLC.
Two hundred and seven drug targets and 5,282 disease targets were imported into Venny 2.1.0, and a total of 160 intersecting targets of ADI and NSCLC (Supplementary Material 3) were obtained fnally. Te Venn diagram of ADI and NSCLC is shown in Figure 2.

DDCT and PPI Network Diagrams.
Tere are a total of 199 nodes and 650 interacting lines in the DDCT network diagram ( Figure 3, Supplementary Material 4). Among the 199 nodes, 37 were active ingredients, 160 were targeted proteins, one was a disease name node, and one was a drug name node. Te top 10 compounds of degrees in the DDCT network diagram are shown in Table 2. Te PPI network graph was obtained from the STRING database, which contained 158 nodes and 2903 interacting lines. We imported the PPI network graph fle into Cytoscape software, screened out the nodes whose degree and BC were greater than their average, and fnally obtained 28 key targets and 352 connecting lines (Table 3). Te PPI diagram of key targets is shown in Figure 4.

GO and KEGG Enrichment
Analysis. GO enrichment analysis mainly describes genes from three aspects, namely, biological process (BP), cellular component (CC), and molecular function (MF). A total of 1850 entries with p < 0.05 of GO enrichment analysis were obtained fnally, which included 1752 BP entries, 21 CC entries, and 77 MF entries (Supplementary Material 5). Te 15 entries closely related to the disease were selected for visualization, respectively. As is shown in Figure 5(a), the results of BP mainly involved epithelial cell proliferation and regulation, Evidence-Based Complementary and Alternative Medicine regulation of angiogenesis, regulation of the DNA metabolic process, and regulation of macro-autophagy. CC mainly included nuclear chromatin, membrane microdomain, membrane region, and vesicle lumen ( Figure 5(b)). MF mainly contained phosphatase binding, cytokine activity, growth factor receptor binding, and growth factor activity ( Figure 5(c)). A total of 145 entries with p < 0.05 of KEGG enrichment analysis were screened (Supplementary Material 6). Te results of KEGG enrichment analysis indicated that multiple signaling pathways were associated with NSCLC, which included the MAPK signaling pathway, the IL-17 signaling pathway, and PI3K/AKT signaling pathway, etc. Te diference in the MAPK signaling pathway is the most obvious. Te 15 entries that were closely related to NSCLC were selected for visualization ( Figure 6). Te key genes in these signaling pathways mainly included TP53, AKT1, CASP3, MMP9, MAPK1, and PTGS2. Te results of the above enrichment analysis suggested that ADI plays an anti-NSCLC role by afecting cell apoptosis, proliferation, migration, and up-regulating or down-regulating the expression of key genes in these signaling pathways.    (Figures 7(a)-7(f )). In LUAD, the expression of TP53, CASP3, MMP9, AKT1, and PTGS2 had statistical diferences compared with normal tissue (p < 0.001) (Figures 7(g)-7(k)), while, the expression of MAPK1 had no statistical diference (p > 0.05) (Figure 7(l)). Compared with normal tissues, TP53, CASP3, and MMP9 were up-regulated in LUSC and LUAD (Figures 7(a)-7(c) and 7(g)-7(i)). Similarly, MAPK1 was up-regulated in LUSC compared with normal tissues (Figure 7(f )). Conversely, AKT1 and PTGS2 were down-regulated in LUSC and LUAD compared with normal tissues (Figures 7(d)-7(e) and 7(j)-7(k)). Tese results indicated that ADI exerted its therapeutic efect by afecting the expression of these key genes in tumor tissue.

Survival Analysis of Key Genes.
In our study, the results of the survival analysis of key genes showed that AKT1, MAPK1, CASP3, MMP9, TP53, and PTGS2 had statistical diferences in the OS or RFS of NSCLC patients (p < 0.05) ( Figure 8). Patients with higher expression of AKT1 had longer OS in LUAD (Figure 8(a)), and MAPK1 had longer OS in LUSC (Figure 8(b)). Patients with lower expression of CASP3 and MMP9 had longer RFS in LUAD (Figures 8(c)  and 8(d)), and similarly, in LUSC, patients with lower expression of TP53 had longer RFS (Figure 8(e)). Conversely, patients with higher expression of PTGS2 had longer RFS in LUSC (Figure 8(f )). Te results of the above survival analysis were consistent with the results of the diferential analysis of key gene expression, which further illustrated the accuracy of the results of this study.

Molecular Docking.
To further verify the accuracy of the results, we performed molecular docking technique on the top 10 compounds in terms of degree in the DDCT network diagram and the top 5 key genes (AKT1, CASP3, MAPK1, PTGS2, and TP53). As shown in Table 4, the results of molecular docking indicated that the lowest binding energy was stigmasterol and AKT1 with a binding energy was −10 kcal/mol. Te most stable binding to CASP3 was kaempferol, and the binding energy was −8.3 kcal/mol. MAPK1 and stigmasterol had the lowest binding energy, which was stigmasterol. Te most stable compounds that bind to PTGS2 and TP53 were quercetin and isorhamnetin, with binding energies of −7.5 kcal/mol and −5.8 kcal/mol, respectively. In addition, we also found that the top 6 binding energies from low to high were AKT1 and stigmasterol, quercetin, kaempferol, hederagenin, calycosin, and beta-sitosterol, respectively, which demonstrated that AKT1 may be a very critical target for ADI in the treatment of NSCLC. Tese results showed that the core compounds and key genes had good binding activity, which further verifed that ADI exerted its therapeutic efect through these key genes. Te top 6 molecular docking patterns in terms of binding energies were shown in Figure 9.

Discussion
NSCLC has no obvious clinical symptoms, and most NSCLC patients are in the advanced stage once diagnosed, with poor prognosis, which seriously threatens human health. In recent years, there have been more and more clinical trials and basic researches on ADI in the treatment of NSCLC, providing a new method for the treatment of NSCLC. Several studies have shown that ADI combined with conventional western medicine treatment can signifcantly improve clinical efcacy and reduce the occurrence of adverse reactions [14][15][16]. In order to promote the visualization and evidence-based research and development of the mechanism, this study systematically analyzed the potential mechanism of ADI in the treatment of NSCLC by using bioinformatics methods.
We found that the main components of ADI were quercetin, formononetin, kaempferol, beta-sitosterol, and       Evidence-Based Complementary and Alternative Medicine of Nrf2 [19]. Gourav Kumar found that beta-sitosterol has good anticancer activity [20]. Studies illustrated that stigmasterol efectively inhibited the activity of A549 nonsmall cell lung cancer [21]. All the above studies had demonstrated that the main components of ADI could exert its antitumor efect via inhibiting the growth of NSCLC tumors or promoting tumor cell apoptosis. Trough the PPI network map, we found that there were 28 key targets of ADI in the treatment of NSCLC, including 6 key genes that existed in the main signaling pathways, which were AKT1, TP53, CASP3, MAPK1, MMP9, and PTGS2. AKT1 was a member of the AKT kinase family, and research showed that AKT1 plays an antimetastatic role in the NSCLC cells with KRAS or EGFR mutations [22]. In addition, AKT1 down-regulation could also increase the sensitivity of NSCLC cells to chemotherapeutic agents [23]. Te TP53 mutation is one of the most common mutated genes in human lung cancer. A large number of studies have shown that TP53 mutation was not only a poor prognostic factor for NSCLC but also increases the resistance of patients with EGFR mutation to EGFR-TKI therapy [24][25][26]. CASP3, which played a crucial role in apoptosis, had been well known. However, it had been found that CASP3 was also an oncogene in recent studies. Hence, target therapy of CASP3 not only increased the sensitivity of cancer cells to chemotherapy and radiotherapy but also inhibited the invasion and metastasis of cancer cells [27,28]. MAPK1 could mediate cell proliferation and metastasis [29,30]. Te MAPK1/ ERK2 pathway was activated in the early stage of lung cancer formation [31], which suggested that MAPK1 is a potentially important target for the early prevention and treatment of NSCLC. In addition, overexpression of MMP9 led to the occurrence of NSCLC, and inhibition of MMP9 could prevent the growth, migration, and invasion of NSCLC cells, so MMP9 is expected to become a therapeutic target for the prevention of NSCLC metastasis [32][33][34]. Studies have also shown that the mechanism of chemotherapy resistance in NSCLC was related to PTGS2 [35]. Te results of these Evidence-Based Complementary and Alternative Medicine studies confrmed that these key targets were closely related to nonsmall cell lung cancer, which was consistent with the results of the diferential expression analysis of key genes in this study. Te results of KEGG enrichment analysis indicated that multiple signaling pathways were involved in the ADI treatment of NSCLC, which included the MAPK signaling pathway, the IL-17 signaling pathway, and PI3K/AKT signaling pathway, etc. Mitogen-activated protein kinase (MAPK) is an important transmitter of signals from the cell surface to the nucleus, which is a group that can be activated by diferent extracellular stimuli, such as cytokines, neurotransmitters, hormones, cell stress, and cell adhesion. Te basic component of the MAPK pathway is a tertiary kinase pattern that is conserved from yeast to humans, including MAP kinase kinase kinase (MKKK), MAP kinase kinase (MKK), and MAPK, which can be activated in turn to jointly regulate cells growth, diferentiation and response to infammation and other important cellular physiological or pathological processes [36]. MAPK signaling pathway is one of the common junction pathways of cell proliferation, stress, infammation, diferentiation, functional synchronization, transformation, apoptosis, and other signal transduction pathways. It transmits extracellular signals to cells through receptors, G proteins, protein kinases, and transcription factors, and participates in cell proliferation, differentiation, canceration, metastasis and apoptosis, etc. [37]. Besides, several studies have shown that the MAPK signaling pathway played a vital role in multicell processes; it is closely related to tumors [38,39]. Overexpression of an epithelial membrane protein could inhibit the growth, migration, and invasion of NSCLC tumor cells, while knockdown of an epithelial membrane protein can enhance cell migration. Besides, epithelial membrane protein overexpression was closely related to the MAPK signaling pathway [40]. It was well known that the overexpression of ETS-homologous factor was associated with poor prognosis of NSCLC patients, and studies shew that the overexpression of ETShomologous factor caused the occurrence of NSCLC through the AKT signaling pathway and the MAPK/ERK signaling pathway [41]. Te TNF signaling pathway could not only induce the occurrence of NSCLC but also promote     tumor cell proliferation and metastasis [42]. It was confrmed that CD47 upregulation in refractory lung tumor models was mediated by the TNF-α/NF-κB1 signaling pathway, and blocking CD47 could enhance anti-tumor efects [43]. Several studies had shown that the PI3K/AKT signaling pathway, not only promoted the proliferation and migration of NSCLC cells but also increased the resistance of NSCLC to cisplatin [44]. Terefore, the PI3K/AKT signaling pathway was also a very important for the treatment of NSCLC. MiR-496 suppresses tumorigenesis via targeting the BDNF-mediated PI3K/Akt signaling pathway in NSCLC had been confrmed [45]. Dieckol inhibiting NSCLC cell proliferation and migration by regulating the PI3K/AKT signaling pathway had also been found [46]. It was well known that immune cells were closely related to the occurrence and development of NSCLC [47]. T cells and B cells are important immune cells, and studies showed immunotherapy targeting T cells or B cells was a very important method of treatment for NSCLC [48,49]. Terefore, ADI may play a therapeutic role through the T cell receptor signaling pathway or the B cell receptor signaling pathway. NF-κB was widely used by eukaryotic cells as a gene regulator to control cell proliferation and cell survival, which can regulate antiapoptotic genes and play an indispensable role in the process of apoptosis. Research showed that miR-449a suppresses tumor growth, migration, and invasion in NSCLC by targeting the HMGB1-mediated NF-κB signaling pathway [50]. VEGF was a highly specifc vascular endothelial cell growth factor that promoted vascular permeability, vascular endothelial cell migration, proliferation, and angiogenesis, providing nutrients and excreting metabolites for tumor growth. Terefore, inhibiting the activation of the VEGF signaling pathway was a very important approach in the treatment of NSCLC. Bevacizumab, the world's frst VEGF inhibitor, had been widely used in the treatment of NSCLC [51,52]. Te signaling pathways involved in all the above research results were closely related to NSCLC, which demonstrated the accuracy of the enrichment analysis results in this study. It is necessary to use the method of survival analysis for the analysis of the occurrence, development, and prognosis of chronic diseases, especially malignant tumors. OS and RFS are two important reference indicators to describe the survival rate. In our study, the results of survival analysis showed that the expression of key genes in the signaling pathway had a signifcant impact on the OS or RFS of NSCLC patients, which verifed the accuracy of the network pharmacology results, and indicated that the antitumor efect of Aidi injection was by upregulating or downregulating the expression of these key genes in tumor tissue. Molecular docking results showed that the main components of ADI and the key genes in the signaling pathway had good binding activity. It is  well known that AKT1 plays an indispensable role in regulating tumor cell proliferation and apoptosis [53]. Interestingly, from the results of molecular docking, we found that the genes involved in the top 6 binding energies are all AKT1. Besides, the components with the lowest binding energies to CASP3, MAPK1, PTGS2, and TP53 were kaempferol, stigmasterol, quercetin, and isorhamnetin. CASP3 as an apoptosis-related gene played a central role in executing cell apoptosis and thus in carcinogenesis [54]. Both MAPK1 and PTGS2 were involved in cell proliferation and invasion, which made them closely related to tumorigenesis [55]. TP53 is well-known as a tumor suppressor gene that induces cell cycle arrest, apoptosis, or senescence [56]. Tese results demonstrated that the main components of ADI work together to exert antitumor efects by inhibiting tumor cell growth, invasion, and metastasis and promoting tumor cell senescence and apoptosis, which perfectly interpreted the overall concept of TCM.

Conclusion
Our results revealed the mechanism of ADI in the treatment of NSCLC may be through the targets of AKT1, TP53, CASP3, MAPK1, and PTGS2, regulating the MAPK signaling pathway, PI3K-AKT signaling pathway, and TNF signaling pathway to exert its therapeutic efect. In conclusion, this study revealed the mechanism of ADI against NSCLC through multipathways and multitargets, which provided new insights for clarifying the molecular mechanism of ADI and also provided a reference for the research and development of anti-NSCLC drugs.

Data Availability
Te original contributions presented in the study are included in the article/supplementary materials; further inquiries can be directed to the corresponding authors.

Conflicts of Interest
Te authors declare that they have no conficts of interest.